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https://github.com/All-Hands-AI/OpenHands.git
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9b371b1b5f
This PR fixes #1897. In addition, this PR fixes and tweaks a few micro-agents. For the first time, I am able to use ManagerAgent to complete test_write_simple_script and test_edits tasks in integration tests, so this PR also adds ManagerAgent as part of integration tests. test_write_simple_script involves delegation to CoderAgent while test_edits involves delegation to TypoFixerAgent. Also for the first time, I am able to use DelegateAgent to complete test_write_simple_script and test_edits tasks in integration tests, so this PR also adds DelegateAgent as part of integration tests. It involves delegation to StudyRepoForTaskAgent, CoderAgent and VerifierAgent. This PR is a blocker for #1735 and likely #1945.
75 lines
2.4 KiB
Python
75 lines
2.4 KiB
Python
from jinja2 import BaseLoader, Environment
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from opendevin.controller.agent import Agent
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from opendevin.controller.state.state import State
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from opendevin.core.utils import json
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from opendevin.events.action import Action
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from opendevin.events.serialization.action import action_from_dict
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from opendevin.events.serialization.event import event_to_memory
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from opendevin.llm.llm import LLM
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from .instructions import instructions
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from .registry import all_microagents
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def parse_response(orig_response: str) -> Action:
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# attempt to load the JSON dict from the response
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action_dict = json.loads(orig_response)
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# load the action from the dict
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return action_from_dict(action_dict)
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def to_json(obj, **kwargs):
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"""
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Serialize an object to str format
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"""
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return json.dumps(obj, **kwargs)
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def history_to_json(obj, **kwargs):
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"""
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Serialize and simplify history to str format
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"""
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if isinstance(obj, list):
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# process history, make it simpler.
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processed_history = []
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for action, observation in obj:
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processed_history.append(
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(event_to_memory(action), event_to_memory(observation))
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)
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return json.dumps(processed_history, **kwargs)
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class MicroAgent(Agent):
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VERSION = '1.0'
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prompt = ''
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agent_definition: dict = {}
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def __init__(self, llm: LLM):
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super().__init__(llm)
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if 'name' not in self.agent_definition:
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raise ValueError('Agent definition must contain a name')
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self.prompt_template = Environment(loader=BaseLoader).from_string(self.prompt)
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self.delegates = all_microagents.copy()
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del self.delegates[self.agent_definition['name']]
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def step(self, state: State) -> Action:
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prompt = self.prompt_template.render(
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state=state,
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instructions=instructions,
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to_json=to_json,
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history_to_json=history_to_json,
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delegates=self.delegates,
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latest_user_message=state.get_current_user_intent(),
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)
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messages = [{'content': prompt, 'role': 'user'}]
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resp = self.llm.do_completion(messages=messages)
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action_resp = resp['choices'][0]['message']['content']
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state.num_of_chars += len(prompt) + len(action_resp)
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action = parse_response(action_resp)
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return action
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def search_memory(self, query: str) -> list[str]:
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return []
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